class_docstr: GPT Language Model
code: def _init_weights(self, module: torch.nn.Module) -> None:
      if isinstance(module, (nn.Linear, nn.Embedding)):
          module.weight.data.normal_(mean=0.0, std=0.02)
          if isinstance(module, nn.Linear) and module.bias is not None:
              module.bias.data.zero_()
      elif isinstance(module, nn.LayerNorm):
          module.bias.data.zero_()
          module.weight.data.fill_(1.0)
  
imports: import math
  from dataclasses import dataclass
  from typing import Optional, Tuple
  import torch
  import torch.nn
  from torch.nn import functional
label_desc: Use image node_id 3 for calling the GPT obj's underlying member method code with example usage: obj._init_weights(module) without return types